Literature DB >> 25778935

Twenty-five years of confirmatory adaptive designs: opportunities and pitfalls.

Peter Bauer1, Frank Bretz2,3, Vladimir Dragalin4, Franz König1, Gernot Wassmer5,6.   

Abstract

'Multistage testing with adaptive designs' was the title of an article by Peter Bauer that appeared 1989 in the German journal Biometrie und Informatik in Medizin und Biologie. The journal does not exist anymore but the methodology found widespread interest in the scientific community over the past 25 years. The use of such multistage adaptive designs raised many controversial discussions from the beginning on, especially after the publication by Bauer and Köhne 1994 in Biometrics: Broad enthusiasm about potential applications of such designs faced critical positions regarding their statistical efficiency. Despite, or possibly because of, this controversy, the methodology and its areas of applications grew steadily over the years, with significant contributions from statisticians working in academia, industry and agencies around the world. In the meantime, such type of adaptive designs have become the subject of two major regulatory guidance documents in the US and Europe and the field is still evolving. Developments are particularly noteworthy in the most important applications of adaptive designs, including sample size reassessment, treatment selection procedures, and population enrichment designs. In this article, we summarize the developments over the past 25 years from different perspectives. We provide a historical overview of the early days, review the key methodological concepts and summarize regulatory and industry perspectives on such designs. Then, we illustrate the application of adaptive designs with three case studies, including unblinded sample size reassessment, adaptive treatment selection, and adaptive endpoint selection. We also discuss the availability of software for evaluating and performing such designs. We conclude with a critical review of how expectations from the beginning were fulfilled, and - if not - discuss potential reasons why this did not happen.
© 2015 The Authors. Statistics in Medicine Published by John Wiley & Sons Ltd.

Entities:  

Keywords:  adaptive design; clinical trials; group sequential designs

Mesh:

Year:  2015        PMID: 25778935      PMCID: PMC6680191          DOI: 10.1002/sim.6472

Source DB:  PubMed          Journal:  Stat Med        ISSN: 0277-6715            Impact factor:   2.373


  115 in total

1.  Graphical approaches for multiple comparison procedures using weighted Bonferroni, Simes, or parametric tests.

Authors:  Frank Bretz; Martin Posch; Ekkehard Glimm; Florian Klinglmueller; Willi Maurer; Kornelius Rohmeyer
Journal:  Biom J       Date:  2011-08-12       Impact factor: 2.207

2.  Adaptive designs in clinical drug development--an Executive Summary of the PhRMA Working Group.

Authors:  Paul Gallo; Christy Chuang-Stein; Vladimir Dragalin; Brenda Gaydos; Michael Krams; José Pinheiro
Journal:  J Biopharm Stat       Date:  2006-05       Impact factor: 1.051

3.  A comparison of methods for adaptive treatment selection.

Authors:  Tim Friede; Nigel Stallard
Journal:  Biom J       Date:  2008-10       Impact factor: 2.207

4.  A group-sequential design for clinical trials with treatment selection.

Authors:  Nigel Stallard; Tim Friede
Journal:  Stat Med       Date:  2008-12-20       Impact factor: 2.373

5.  Exact inference for adaptive group sequential designs.

Authors:  Ping Gao; Lingyun Liu; Cyrus Mehta
Journal:  Stat Med       Date:  2013-05-19       Impact factor: 2.373

6.  Optimal restricted two-stage designs.

Authors:  L D Case; T M Morgan; C E Davis
Journal:  Control Clin Trials       Date:  1987-06

7.  Confirmatory adaptive designs with Bayesian decision tools for a targeted therapy in oncology.

Authors:  Werner Brannath; Emmanuel Zuber; Michael Branson; Frank Bretz; Paul Gallo; Martin Posch; Amy Racine-Poon
Journal:  Stat Med       Date:  2009-05-01       Impact factor: 2.373

8.  An approach to the conditional error rate principle with nuisance parameters.

Authors:  Georg Gutjahr; Werner Brannath; Peter Bauer
Journal:  Biometrics       Date:  2010-11-29       Impact factor: 2.571

9.  Connections between permutation and t-tests: relevance to adaptive methods.

Authors:  Michael Proschan; Ekkehard Glimm; Martin Posch
Journal:  Stat Med       Date:  2014-08-25       Impact factor: 2.373

Review 10.  Adaptive clinical trial designs for European marketing authorization: a survey of scientific advice letters from the European Medicines Agency.

Authors:  Amelie Elsäßer; Jan Regnstrom; Thorsten Vetter; Franz Koenig; Robert James Hemmings; Martina Greco; Marisa Papaluca-Amati; Martin Posch
Journal:  Trials       Date:  2014-10-02       Impact factor: 2.279

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  48 in total

1.  The Adaptive designs CONSORT Extension (ACE) statement: a checklist with explanation and elaboration guideline for reporting randomised trials that use an adaptive design.

Authors:  Munyaradzi Dimairo; Philip Pallmann; James Wason; Susan Todd; Thomas Jaki; Steven A Julious; Adrian P Mander; Christopher J Weir; Franz Koenig; Marc K Walton; Jon P Nicholl; Elizabeth Coates; Katie Biggs; Toshimitsu Hamasaki; Michael A Proschan; John A Scott; Yuki Ando; Daniel Hind; Douglas G Altman
Journal:  BMJ       Date:  2020-06-17

2.  Two-stage adaptive enrichment design for testing an active factor.

Authors:  A Adam Ding; Samuel S Wu; Natalie E Dean; Rachel S Zahigian
Journal:  J Biopharm Stat       Date:  2019-05-28       Impact factor: 1.051

3.  Using Bayesian modeling in frequentist adaptive enrichment designs.

Authors:  Noah Simon; Richard Simon
Journal:  Biostatistics       Date:  2018-01-01       Impact factor: 5.899

4.  Simulation optimization for Bayesian multi-arm multi-stage clinical trial with binary endpoints.

Authors:  Zhenning Yu; Viswanathan Ramakrishnan; Caitlyn Meinzer
Journal:  J Biopharm Stat       Date:  2019-02-14       Impact factor: 1.051

Review 5.  Adaptive trial designs for spinal cord injury clinical trials directed to the central nervous system.

Authors:  James D Guest; John D Steeves; M J Mulcahey; Linda A T Jones; Frank Rockhold; Rϋediger Rupp; John L K Kramer; Steven Kirshblum; Andrew Blight; Daniel Lammertse
Journal:  Spinal Cord       Date:  2020-09-16       Impact factor: 2.772

Review 6.  Adaptive Designs for Clinical Trials: Application to Healthcare Epidemiology Research.

Authors:  W Charles Huskins; Vance G Fowler; Scott Evans
Journal:  Clin Infect Dis       Date:  2018-03-19       Impact factor: 9.079

Review 7.  Essential statistical principles of clinical trials of pain treatments.

Authors:  Robert H Dworkin; Scott R Evans; Omar Mbowe; Michael P McDermott
Journal:  Pain Rep       Date:  2020-12-18

8.  Using the Bayesian credible subgroups method to identify populations benefiting from treatment: An application to the Look AHEAD trial.

Authors:  Anna Coonan; Patrick Schnell; Joel Smith; John Forbes
Journal:  PLoS One       Date:  2020-04-21       Impact factor: 3.240

9.  A post hoc evaluation of a sample size re-estimation in the Secondary Prevention of Small Subcortical Strokes study.

Authors:  Leslie A McClure; Jeff M Szychowski; Oscar Benavente; Robert G Hart; Christopher S Coffey
Journal:  Clin Trials       Date:  2016-04-19       Impact factor: 2.486

10.  Accounting for selection and correlation in the analysis of two-stage genome-wide association studies.

Authors:  David S Robertson; A Toby Prevost; Jack Bowden
Journal:  Biostatistics       Date:  2016-03-18       Impact factor: 5.899

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